{"id":"W2970132222","doi":"10.1111/bcp.14104","title":"Impact of medicines regulatory risk communications in the UK on prescribing and clinical outcomes: Systematic review, time series analysis and meta‐analysis","year":2019,"lang":"en","type":"review","venue":"British Journal of Clinical Pharmacology","topic":"Pharmacovigilance and Adverse Drug Reactions","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Global Health Research","funders":"","keywords":"Confidence interval; Medicine; Relative risk; Meta-analysis; Interrupted Time Series Analysis; Family medicine; Internal medicine; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.01978836,0.0005919273,0.01442302,0.0009107887,0.0002151927,0.00003711757,0.001458146,0.0007901541,0.0007599847],"category_scores_gemma":[0.002872712,0.0003811404,0.008937808,0.001693043,0.001222554,0.0002302963,0.0002763199,0.00532547,0.00001903268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007063782,"about_ca_system_score_gemma":0.0004891579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007869497,"about_ca_topic_score_gemma":0.00007594658,"domain_scores_codex":[0.9726959,0.01901359,0.006894084,0.0005475323,0.0004316666,0.0004171982],"domain_scores_gemma":[0.963769,0.02743669,0.007258893,0.0007680181,0.0003838382,0.0003835087],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.0002194578,0.001782123,0.02452497,0.06620668,0.8836114,0.0003327272,0.00007500424,0.000149704,7.360644e-7,0.00001221366,0.009390186,0.01369478],"study_design_scores_gemma":[0.001503923,0.0004124831,0.008733821,0.006323403,0.9635197,0.0005214006,0.00002918944,0.0001335058,1.602403e-7,0.00002190571,0.01848236,0.0003181681],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.003734036,0.9923766,0.000005223198,0.0004969366,0.0005663333,0.001962857,0.0007106256,0.00001214327,0.0001353004],"genre_scores_gemma":[0.007072551,0.9897514,0.00005717828,0.002558308,0.0002074906,0.00008977917,0.00006831231,0.00003201275,0.0001629639],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.07990826,"threshold_uncertainty_score":0.999864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.342949846412742,"score_gpt":0.5975179890362511,"score_spread":0.2545681426235091,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}